ThesisPDF Available

ACCEPTANCE OF RIDE SHARING SERVICE BY STRUCTURAL EQUATION MODELING

May 2021

Authors:

Military Institute of Science and Technology

Application based ride sharing service is reducing traffic congestion and providing employment opportunity to the people. Easy to access nature and due to comfortability this service is becoming popular in Bangladesh. The service providers and policymakers are trying to expand this ride sharing service for different people travelling to the same destination. In this study overall acceptance of ride sharing service is measured with sharing attitude and perceived risk of user’s. For this study structured questions were formed based on reported attitude and perceived risk of the users from literature and stake holders. Using online survey total 350 data was collected from car sharing users of Bangladesh. Our study shows that, the data collected from ride sharing users are consistent and suitable for factor analysis. Data is incorporated with structural equation model to test the hypothesis of service acceptance of ride sharing service. The structural equation model is justified with the help of SPSS Amos 26. Our result shows that, safety & security of ride sharing service and user’s judgement those were latent variables in the developed model have positive influence with each other. Under user’s judgement latent variable, driver’s attitude(y7), driver’s skill(y8), traffic congestion(y9) and environmental impact(y10) observed variables has higher influence on ride sharing service. One the other hand, under safety & security latent variable, personal info. (y11) and account info. (y12) observed variables has higher influence on sharing attitude. Our results also signify deeper understanding of the effect of user’s sharing attitude and perceived risk on their acceptance of ride sharing service. These findings help the policy makers to understand the key attributes of sharing attitude of the user’s. These results can also be utilized by the service provider and policy maker to improve the service quality to attract new user’s and the existing user’s. Driver’s skill, driver’s attitude toward user’s during traffic congestion and use of environment friendly fuel can help the policy maker to make this service more acceptable. And also privacy of both user’s info. and user’s account info. can accelerate this service. Our study also found ride sharing service more time and cost affordable for all type of users than public transport. By making ride sharing application more user-friendly and availability of ride sharing vehicles during peak hour this service can be widely accepted service for all.

Traffic jam in Dhaka city

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Gender difference of respondents

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Reliability & validity relations

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Comfortability of user's during sharing his/her rides

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Time affordability during peak hour Ride sharing service main purpose is to travel at any place at low price. But the fare of public

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Content uploaded by Md. Mohaimenul Islam Sourav

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ACCEPTANCE OF RIDE SHARING SERVICE BY

STRUCTURAL EQUATION MODELING

MD. MOHAIMENUL ISLAM SOURAV

TAMANNA TABASSUM

MD MAHEDI HASAN OPU

A THESIS SUBMITTED

FOR THE DEGREE OF BACHELOR OF SCIENCE

DEPARTMENT OF CIVIL ENGINEERING

MILITARY INSTITUTE OF SCIENCE AND TECHNOLOGY

2021

SUPERVISOR’S APPROVAL

The thesis titled, “ACCEPTANCE OF RIDE SHARING SERVICE BY STRUCTURAL

EQUATION MODELING” prepared by Md. Mohaimenul Islam Sourav, Roll No: 201711024,

Tamanna Tabassum, Roll No: 201711046 and Md Mahedi Hasan Opu, Roll No: 201611079,

Session: 2016-17 has been approved for submission in partial fulfilment of the required for the

Degree of Bachelor of Science in Civil Engineering.

Lt Col Mohammed Russedul Islam, PhD, Engrs

Associate Professor

Department of Civil Engineering

Military Institute of Science and Technology

DECLARATION

We hereby declare that, this thesis is our original work and it has been written by us in it’s

entirely. We have duly acknowledged all the sources of information which have been used in

the thesis. The thesis (fully or partially) has not been submitted for any degree or diploma in

any university or institute previously.

Md. Mohaimenul Islam Sourav

Student ID: 201711024

Department of Civil Engineering

Military Institute of Science and Technology

Tamanna Tabassum

Student ID: 201711046

Department of Civil Engineering

Military Institute of Science and Technology

Md Mahedi Hasan Opu

Student ID: 201611079

Department of Civil Engineering

Military Institute of Science and Technology

DEDICATION

This thesis work is dedicated to our beloved parents.

ACKNOWLEDGEMENT

First of all, we are indebted to the almighty Allah for overwhelming all the obstacles and

predicament that faced during the whole research work and for bringing this thesis into its

authenticity.

We would like to thank our supervisor, Associate Professor Lt Col Mohammed Russedul Islam,

PhD, Engrs, for his guidance, advice and encouragement during the course of this thesis.

Without his time and knowledge, this research would not have been possible.

We would also like to express our profound gratitude to Major H. M. Imran Kays, Engrs,

Assistant Professor of Military Institute of Science and Technology for giving unparalleled

support to our experiment.

Special thanks to those respondents who answered our research questions.

Abstract

ABSTRACT

Application based ride sharing service is reducing traffic congestion and providing

employment opportunity to the people. Easy to access nature and due to comfortability this

service is becoming popular in Bangladesh. The service providers and policymakers are trying

to expand this ride sharing service for different people travelling to the same destination. In

this study overall acceptance of ride sharing service is measured with sharing attitude and

perceived risk of user’s. For this study structured questions were formed based on reported

attitude and perceived risk of the users from literature and stake holders. Using online survey

total 350 data was collected from car sharing users of Bangladesh. Our study shows that, the

data collected from ride sharing users are consistent and suitable for factor analysis. Data is

incorporated with structural equation model to test the hypothesis of service acceptance of ride

sharing service. The structural equation model is justified with the help of SPSS Amos 26. Our

result shows that, safety & security of ride sharing service and user’s judgement those were

latent variables in the developed model have positive influence with each other. Under user’s

judgement latent variable, driver’s attitude(y7), driver’s skill(y8), traffic congestion(y9) and

environmental impact(y10) observed variables has higher influence on ride sharing service.

One the other hand, under safety & security latent variable, personal info. (y11) and account

info. (y12) observed variables has higher influence on sharing attitude. Our results also signify

deeper understanding of the effect of user’s sharing attitude and perceived risk on their

acceptance of ride sharing service. These findings help the policy makers to understand the key

attributes of sharing attitude of the user’s. These results can also be utilized by the service

provider and policy maker to improve the service quality to attract new user’s and the existing

user’s. Driver’s skill, driver’s attitude toward user’s during traffic congestion and use of

environment friendly fuel can help the policy maker to make this service more acceptable. And

Abstract

also privacy of both user’s info. and user’s account info. can accelerate this service. Our study

also found ride sharing service more time and cost affordable for all type of users than public

transport. By making ride sharing application more user-friendly and availability of ride

sharing vehicles during peak hour this service can be widely accepted service for all.

Key Words: Sharing attitude, Perceived risk, Service Acceptance, Data suitability and

consistency, Structural Equation Modeling

Abstract

iii

Table of Contents

iii

TABLE OF CONTENTS

Page No.

ABSTRACT i

TABLE OF CONTENTS iii

LIST OF ABRIVIATION vi

LIST OF FIGURES ix

LIST OF TABLES xii

CHAPTER ONE: INTRODUCTION

1.1 Background 01

1.2 Concept of Ride Sharing Service 04

1.3 Objectives 07

1.4 Scope of The Work 07

1.5 Organization of Thesis 08

CHAPTER TWO: LITERATURE REVIEW

2.1 Introduction 10

2.2 Concept of Ride Sharing 10

2.3 Previous Study on Ride Sharing Service 11

Table of Contents

2.4 Previous Study on SEM 16

CHAPTER THREE: METHODOLOGY

3.1 Introduction 18

3.2 Steps of Work 18

3.3 Study Methodology 19

3.3.1 Selection of service acceptance variables 20

3.3.2 Questionnaire structure 23

3.3.3 Sample size 23

3.4 SEM for Analysis 27

3.5 Conceptual Framework of Structural Equation Model 29

3.6 Empirical Model 30

3.7 Structural Equation Model 33

CHAPTER FOUR: DATA DESCRIPTION AND PRELIMINARY STATICS

4.1 Introduction 36

4.2 Survey Context 36

4.3 Sample Characteristics 36

Table of Contents

CHAPTER FIVE: RESULT AND DISCUSSION

5.1 Introduction 42

5.2 Factor Analysis Results 42

5.2.1 Exploratory factor analysis 42

5.2.2 Confirmatory factor analysis 43

5.2.2.1 Validity concerns 45

5.3 Hypothesis Testing Results 46

5.4 Empirical Model Results 50

5.5 Discussion 60

CHAPTER SIX: CONCLUSION AND RECOMMENDATIONS

6.1 Introduction 64

6.2 Conclusions 64

6.3 Recommendations for Future Research 65

REFERENCE 67

List of Symbols

LIST OF ABBREVIATIONS

GDP Gross domestic products

WHO World Health Organization

PM Particulate matter

GPS Global positioning system

SA Service acceptance

CO2 Carbon-di-Oxide

RS Ride sharing

SEM Structural Equation Modeling

SAV Shared and automated vehicles

DRS Direct rail services

CC Charges collect

NL Nested logit

KMO Kaiser-Meyer-Olkin

CFI Comparative fit index

NFI Normed fit index

TLI Tucker-Lewis index

RMSEA Root mean squared error of approximation

List of Symbols

vii

SRMSR Standardized root mean squared residual

AIC Akaike’s information criterion

UE User’s experience

AP Acceptance

WL Willingness

ST Safety

AT Accessibility

SM Security of money

BRTC Bangladesh road transport authority

CFA Confirmatory factor analysis

EFA Explanatory factor analysis

df Degree of freedom

AVE Average variance extracted

CR Composite reliability

S.E Standard error

p Conventional level of significance

CNG Compressed natural gas

List of Symbols

viii

List of Figures

LIST OF FIGURES

Page No.

Figure 1.1 Traffic jam in Dhaka city 02

Figure 1.2 Air pollution in Dhaka city 02

Figure 1.3 Public transport condition in Dhaka city 03

Figure 1.4 Women facing difficulties in public transport 04

Figure 1.5 Ride sharing service in Bangladesh 05

Figure 3.1 Flow diagram of research work 19

Figure 3.2 Conceptual framework of structural model 29

Figure 3.3 Confirmatory factor analysis 32

Figure 3.4 Structural model 35

Figure 4.1 Gender difference of respondents 37

Figure 4.2 Age difference of respondents 37

Figure 4.3 Occupational status of respondents 38

Figure 4.4 Mostly visited place 39

Figure 4.5 Living place of respondents 39

Figure 4.6 Daily travel distance of respondents 40

Figure 4.7 Trip purposes 40

Figure 4.8 Reasons of ride sharing 41

List of Figures

Figure 5.1 Reliability & validity relations 46

Figure 5.2 Hypothesis result of structural model 47

Figure 5.3 Comfortability of user’s during sharing his/her rides 52

Figure 5.4 Time affordability during peak hour 53

Figure 5.5 Cost affordability while sharing the rides with others than 53

travelling alone

Figure 5.6 Familiarity with ride sharing application 54

Figure 5.7 Availability of ride sharing vehicles during peak hour 54

Figure 5.8 Driver’s skill both in free flow & congested condition 55

Figure 5.9 Traffic congestion during peak hour 55

Figure 5.10 Environmental impact due to use of fuel 56

Figure 5.11 Support ride sharing services as it takes credit card/ bKash/ 56

rocket account information

Figure 5.12 Allowing personal car for “Ride sharing” service while it 57

remains Idle

Figure 5.13 Overall safety of “ride Sharing” service 57

Figure 5.14 Women safety during sharing her rides at night 58

Figure 5.15 Possibilities of accident while using “Ride sharing” service 58

Figure 5.16 Possibilities of being deceived due to fare payment. 59

Figure 5.17 Possibilities of conflict while paying the fare among the user’s 60

List of Figures

List of Tables

xii

LIST OF TABLES

Page No.

Table 3.1 List of service acceptance variables 21

Table 3.2 Preliminary statistics of research data 24

Table 4.1 Income distribution of respondents 38

Table 5.1 KMO and Bartlett’s test 43

Table 5.2 Cronbach’s alpha test 43

Table 5.3 Model fit result of CFA model 44

Table 5.4 Validity and reliability test result 44

Table 5.5 Confirmatory factor analysis result 45

Table 5.6 Estimated parameters value of diff. SA variables 48

Table 5.7 Goodness of fit measures of models 51

List of Tables

xiii

Introduction

CHAPTER ONE

INTRODUCTION

1.1 Background

With the development of civilization Bangladesh has become a developing country with per

head income of 1274 US Dollar, Human resource Index of 72 and Economic Crisis Index is

25.2. Transportation system is the prime element that has most contribution in our economy.

Transportation system playing major role in our economy. Due to improvement of

transportation system it is assumed to obtain GDP up to 0.660 by 2025(Sourav & Islam, 2021).

The transportation system of Bangladesh is improving rapidly but still has many flaws which

hampers the development of the country. It needs Improvement with enough safety standards

to meet the demand of people. The severe traffic congestion in Dhaka city in Fig. 1.1 is one of

the major problems in our country but still no organization is taking the responsibility for

solving the problem. A huge population is making the existing public transport inefficient and

creating problems like sound pollution, air pollution etc. And making the roads crowd and

unsafe (Rahman & Nahrin, 2012).

Environmental issue is one of the major issues in our country. Most of the vehicles operating

in our country don’t use environmental friendly fuel. As a result, our environment is being

polluted daily in Fig. 1.2 (Agatz et al. 2012; Naik & Mohanta, 2020). According to WHO report

Dhaka reaches a yearly average of 90 µg/m3 of PM2.5, which corresponds to a 168-unhealthy

air quality index (Wang et al. 2020; Jeon, Lee & Jeong 2020).

Introduction

Fig. 1.1: Traffic jam in Dhaka city

Fig. 1.2: Air pollution in Dhaka city

Road accident is a major problem in our country. Major causes of road accident in our country

in Fig. 1.3 is speeding, overtaking and overloading of passengers, Lack of awareness and

Introduction

reckless driving habit is the main cause of accident. About 5000 people were killed by road

accident in last year (Ahmed, Ahmed & Hainin, 2014).

Fig. 1.3: Public transport condition in Dhaka city

Although the government has already taken some steps, still death counts in highways are

increasing rapidly in an alarming rate. Over speeding, overloaded vehicles, vehicles moving in

the same route are causing these accidents. Driver’s lack of awareness and reckless driving are

also major reasons. The bus drivers in our country are not qualified enough and are not trained

enough to drive in highways. For economic reasons most of the people in Dhaka city are

walking dependent and a large number of people use bicycles and rickshaws to travel but still

there is always a conflict between motorized and non-motorized transports. For these reasons

the current transportation system is not reaching to fulfil the demand of public to have a safe

road and transport system. Safety for women in public transport is also an alarming issue. In

our country there aren’t adequate arrangement for women. A few busses are there but the

proportion is quite low considering the demand. Women often get harassed by men or staff.

Introduction

Sometimes women can’t bargain with the contactor about the actual fare. At night travelling in

public transport system is like a deadly situation for women. Frequently, women passengers

face some unwanted situation (Rahman, 2010). In Fig. 1.4 difficulties are faced by women

getting into public transport is shown.

Fig. 1.4: Women facing difficulties in public transport

As a large number of people are poor in Bangladesh, they can't afford individual rides with

high expenses. So, public transports mainly the buses are the only transport system they can

ride with low cost. But with the increasing population the buses are getting overloaded which

is not safe for the passengers. And also for the poor planning and management bus services are

not satisfactory to meet public demands.

1.2 Concept of Ride Sharing Service

In Fig. 1.5 application based ride sharing can be very useful to reduce traffic congestion and

parking demands for the developing countries like Bangladesh. Ride sharing is mainly

dependent on the willingness of people to share a ride when their destination is same. Ride

Introduction

sharing is developing rapidly with the development of mobile internet technology and other

innovative technologies like GPS (global positioning system) (Wang et al. 2019; Agatz et al.

2011). In our country, during the peak hours' people keep searching for public transports which

makes the road crowd and also it is not always possible to find a comfortable ride for passengers

in those overloaded public transports. In these situations, ride sharing can be a very useful and

effective way to have a comfortable ride. Public transports are not always comfortable so many

aged people can't take

any ride but in ridesharing they can easily travel as they are enough comfortable.

Fig. 1.5: Ride sharing service in Bangladesh

As people share a ride, they don’t need to bear the full travel cost so ride sharing is also cost

effective. Nowadays paratransit is a common term which is also known as community transport

for transportation services. It provides ride without fixed routes or time. The most common

paratransit in Bangladesh is tempo which is highly popular in this time. Although in urban

areas public busses are seen everywhere, it often fails to meet the public demand and also it

has a defined route. In this case paratransit can play very important role in ride sharing as it

doesn’t follow any defined route (Rahman et al. 2016). Moreover, as many people will share a

Introduction

ride the number of vehicles will be reduced in the roads so there will be very less chance to

conflict and the number of accidents will be under control.

The majority of women in Bangladesh are now self-dependent and they are doing different

kind of jobs for their living. They also need to travel to go to their job places regularly. As the

most low-cost transport system is now the public buses, they don’t have any other choices

rather than to travel in those over crowd buses. Travelling in those overly crowded buses are

not comfortable and often not safe for them but still they don’t have any other options because

they must reach to their destination. They need to face many problems during the rides and it

is difficult for them to compete with the men and getting into the buses in the rush hours. So,

they often choose walking to reach their destination which is difficult and requires more time.

Ride sharing can be very useful for them because it is comparatively safer and more

comfortable. They can easily make a group and share a ride with less expenses and safely reach

to their destination without getting late. Service Acceptance is a very important term for ride

sharing. Sometimes a transport system may have a lot of advantages but still may not satisfy

public demand and satisfaction. SA mainly refers to user’s judgment, expectations and

satisfaction. So, a good concept about SA can give a good prediction about the willingness of

people to adopt rideshare in future (Rahman et al. 2016).

Ride sharing is beneficial not only by meeting public demands and sharing travel expenses, by

reducing traffic jams, air pollution, energy consumption ride sharing can also bring social

benefits. It brings environmental benefits by reducing CO2 and energy consumption. It makes

a proper planning for the empty transport seats which improves the travel efficiency and vehicle

capacity (Beria et al. 2017; Wang et al. 2019). In a ride sharing app, when the passengers select

a destination and the driver agrees to that proposal, the app automatically shows the travel fee

to the passenger so there is less chance of conflict between the rider and the driver (Agatz et

al. 2011; Amirkiaee & Evangepoulos, 2018).

Introduction

The relationship of perceived risk and the willingness of people is very important. As maximum

ride sharing is mainly internet based, many personal information is need to be shared thought

internet which is not always considered safe for all the passengers. These risks affect their

willingness of future ride sharing decisions (Wang et al. 2019).

Ride sharing behaviour is dependent on the people’s thought about the ride sharing service they

are being provided, their satisfaction level about the ride, their comfort level while sharing the

ride with strangers etc. and these things influence their willingness to use ride sharing in future

(Moody, Middleton & Zhao, 2019).

1.3 Objectives

1. To identify overall service acceptance of ride sharing service considering user's attitude

and perceived risk.

2. To justify the relationship among the variables using Structural Equation Modeling

1.4 Scope of The Study

The model prepared through this research can be used by the operators and decision makers as

a tool to evaluate SA of Ride Sharing service based on user’s attitude toward sharing ride

considering perceived risk. Most of the ride sharing is only personal. People travel all alone.

Hence, to attract user’s travelling at the same destination and maintain safety standards the

policy maker can use this tool to monitor, evaluate and implement improvements in SA.

In this study total twenty observed variables is used to understand the sharing attitude of the

user’s. Also, through the influence of SA variable on overall perceived SA, the transit agencies

policy makers can identify those critical or important variables that contribute more towards

evaluation of SA. Hence, by prioritizing those variables and improving or developing those,

Introduction

may increase the overall SA drastically. In this way, quick results can be achieved in attracting

potential users of the service.

1.5 Organization of Thesis

The works perform in this thesis are divided into different segments and are presented into six

chapters.

Chapter 1 - A detailed introduction is given about the thesis topic in chapter one with the

objectives, research methodology and the scope of the study.

Chapter 2 - It reviews the relevant researches available that use Structural Equation Modeling

technique as well as other methodology for analysing the Service Acceptance of Ride Sharing

system. A description of SEM technique is also provided at this chapter.

Chapter 3 - Presents a description of the conceptual modelling framework for the causal

relationship to be tested and the hypotheses that are being tested in this research.

Chapter 4 - Presents a brief description of socio-economic as well as Ride Sharing service

acceptance data collected on both users and non-users of Bangladesh and describe how the data

is processed for model estimation. It also provides preliminary statistical parameters of the

collected dataset.

Chapter 5 - Presents the details of different empirical models fitness along with the

significance of model parameters. A detail assessment on model parameter values and its causal

relationship with Ride Sharing passenger vessel SA are also presented in this chapter.

Chapter 6 - Summarizes the main findings of the thesis with some recommendations for future

research.

Introduction

Literature Review

CHAPTER TWO

LITERATURE REVIEW

2.1 Introduction

Review of literature is very important before entering into the process to attain the specific

objectives of the thesis work. It helps to understand and get the overall idea about the topic to

work on. So, it is necessary to conduct a review of literature on the subject matter of thesis.

This chapter presents an extensive review of literatures that deal with different measures or

techniques and variables used to assess the overall perceived service acceptance of ride sharing

system. With a brief description of ride sharing system of Bangladesh, this chapter summarizes

the findings from previous studies on ride sharing service quality analysis. Structural Equation

Modeling technique which has been widely used in transportation industry for SA

measurement. This shows the potential application of SEM in perceived SA assessment of ride

sharing system.

2.2 Concept of Ride Sharing

Fitness less public transport has made the life of public miserable. Overcrowd during peak hour

and waiting at the same station for long time is wasting passengers valuable time. Using of un-

environmental friendly fuel also cause the degradation of environment. Competition of picking

up passengers also cause frequent accident. The development of algorithms for optimally

matching drivers and riders in real-time is at the heart of the ride-sharing concept (Agatz et al.

2012). Ride sharing is a facility and time oriented transportation service using secure and

advantageous technology in real-time ride sharing where two groups of people as driver and

passenger exists (Agatz et al., 2011). This service mostly involves feasible use of vehicles with

a different mode of transportation, usually car and bike. Now, this service only allowing single

Literature Review 
11 
 
user’s to travel any destination. There are no particular vehicle operating organization for ride 
sharing service. Most of the vehicles are personal vehicles. Drivers only allow those user’s to 
share their rides whose  destination is  same as the vehicles  owner. There  is no  free willing 
service provider who will go anywhere the user is willing to go. The main research objective 
is that, by satisfying user’s judgement & safety of ride sharing service accepting someone for 
sharing rides going at the same destination. Therefore, transportation industries can be changed 
by this network companies using updated technology to address the present demand of new 
generation like reduced travel time, travel cost and traffic congestion (Hair et al. 2006; Hooper 
et al. 2008). This research says that, this service has high level of acceptance among the user’s 
travelling  at  the  same  destination.  This  research  has  also  acceptance  in  reducing  traffic 
congestion, saving time and safety during travelling specially for women. 
 
2.3 Previous Study on Ride Sharing Service 
In the  world,  a large  number of studies  are  carried  on  Ride Sharing  for assessing SA or 
investigating passenger satisfaction. Findings from few such studies are presented below. There 
is    no  significant relationship  between rider-to-rider  discriminatory  attitudes  and  whether 
a transportation network companies  user  has  ever  used  a ridesharing  service (Moody, 
Middleton & Zhao 2019) and Hawapi et al. (2017) have found at the neighbourhood level while 
larger  values  of  average degree  centrality of  the road  network are  associated  with 
better Uber accessibility,  higher  values  of  average closeness  centrality are  associated  with 
worse Uber accessibility. 
Hong et al. (2017)  aimed to investigate how a firm’s corporate social responsibility practices 
affect  customers’ attitudes,  their  self-brand connection, and,  in turn, brand preference with 
ridesharing services. By applying a non-negative matrix factorization method, (Golob, 2003; 

Literature Review 
12 
 
Hwang  &  Griftiths,  2017)  found  that, ride-sharing principally  serves  as  an  approach  for 
commuting. Agatz et al. (2011) considers the problem of matching drivers and riders in this 
dynamic setting. Flexible carpooling Casual Carpooling Raspberry Express Slugging. Hume 
(2010)  presents  both  a  classification  of  existing  ridesharing  systems  and  some  specific 
challenges toward  a  mass  fiction of  ridesharing  that  pose  opportunities  for new  research. 
Hawlitschek, Teubner & Gimpel  (2016) article forms a basis for future survey-based research 
on user behavior in the “Sharing Economy.” 
Based  on  the  insight  that Information  and  Communication  Technologies can 
reduce transaction costs and that local geographical knowledge is spread across distant users, 
we have focused on a community-based toolkit as promising technology to reduce transaction 
costs  (Hansen  et  al.  2010). Based  on  the  insight  that Information  and  Communication 
Technologies can reduce transaction costs  and that  local geographical knowledge  is spread 
across distant users, we have focused on a community-based toolkit as promising technology 
to reduce transaction costs (Hansen et al. 2010). 
Hong (2017)  extends the theory of perceived risk in technology acceptance by incorporating 
social concerns which  have received  limited  attention in previous literature  on the sharing 
economy. Hong et al.( 2017) proposed that a modeling and simulation framework  is capable 
of helping achieve this goal and evaluating the traffic state with ride-sharing behaviors. Jin et 
al.  (2018 ) presents a systematic review of the existing literature concerning the impact of ride 
sourcing on the efficiency, equity, and sustainability of urban development. Drawing on the 
extended valence framework, Lee et al. (2018); Gurumurthy &  Kockelman, 2020 propose and 
test  a research  model  to systematically  examine  the effects  of  perceived  risks,  perceived 
benefits, and trust in the platform on users’ intention to participate in the sharing economy. 
In the carpooling case in which pick-up waiting time is less than 1 min, traffic condition in 
82.5%  of  the  congested  road  segments  can  be  alleviated,  and  travel  speed  improvement 

Literature Review 
13 
 
resulting  from  real-time carpooling is  considerable  (Li,  Liu  &  Zhang  2018).  By  taking 
advantage  of  the  different  entry  times  of Uber into  different urban  areas,  Kline  (2011); 
Furuhata  (2013) School  of  Business  are  able  to  compare  the  difference  in traffic 
congestion after and before Uber entry for the urban areas  where Uber operates to  the same 
difference for those urban areas without Uber service. 
In  order  to  compare  the  impact  of ride  sharing using  autonomous  and  traditional  taxis, 
Lokhandwala & Cai (2018) modeled the change of shifts for the traditional taxis to have shift 
schedules that are similar to the existing New York City taxi operation schedules. All personal 
vehicle sharing  and traditional car sharing experts interviewed in the  study and agreed that 
personal vehicle sharing holds the potential to notably expand the shared-use vehicle market 
(Shaheen, Mallery & Kingsley 2012). 
Dong  et  al.  (2018);  Stoiber  et  al.  (2019)    investigated  the  influence  of 
potential instruments designed to encourage the adoption of pooled utilization of autonomous 
vehicles and discourage private ownership of autonomous cars. Wang et al. (2018)  showed 
that environmental awareness is positively associated with  consumers’ intention to use ride-
sharing services. Teubner & Flath (2015) explored the novel idea of multichip ride sharing and 
illustrates  how information  systems  can  leverage  its potential.  Kiatkawsin  & Han  (2017) 
investigated the  environmental benefits  of ride-sharing through its CO2 emission mitigation 
potential. Zhang et al. (2015) developed a simulation model to evaluate the potential impact of 
Shared Autonomous Vehicles on urban parking demand. 
Coook et  al. (2018) suggests that jobs  offering complete  flexibility will likely still contain 
a gender wage gap, much like the traditional workforce. Middleton & Zhao (2019) showed that 
the  attitudinal  finding  is  that  discriminatory  attitudes  toward  fellow  passengers  of 
differing class and race in the shared ride are positively correlated with respondents that are 

Literature Review 
14 
 
male or are women with children. Sarriera et al. (2017) focused on the social and behavioral 
considerations of shared rides, which have not been explored as thoroughly as time and cost 
trade-offs in transportation. The exploratory factor analysis revealed six factors that affected 
the satisfaction of tourists using  bicycle  sharing  ease  of  access  to  cycles,  perceived 
risk, environmental awareness, psychological benefit, managerial effectiveness, and perceived 
rule adherence (Zhou et al. 2020 ). 
Fagnant & Kockelman (2014) focuses on SAVs’ travel and environmental implications, and 
uses  different  assumptions to  model  a much  smaller  share  of such  trips,  while modeling 
directional distribution effects by time of day. Deakin, Frick & Shively (2010); Lee, Lee & 
Yoo  (2019)    builds  on  gaps  in  past  public  AV-perception  studies  by  emphasizing 
ethics, privacy, the nuances of dynamic ride-sharing . Respondents, who traveled by car as 
driver on the reference trip, are relatively more likely to choose the option shared autonomous 
vehicles  without  dynamic  ride-sharing,  while selecting  the  option SAV with DRS is  more 
likely if the  reference trip was undertaken  by car as passenger  (Chang, Lee  & Lee, 2009; 
Krueger, Rashidi & Rose 2016). Uber is one of the popular ride-sharing service, but future 
research can include the study of all major ride sharing services  (Lee, Rahafrooz & Lee, 2017). 
Lyft and Uber drivers are younger than both taxi drivers and the county as a whole; over half 
of ride hail drivers in Los Angeles are under 40 years old compared to about one-third of taxi 
drivers (Li et al. 2016; Cook et al. 2018). 
Marsh, Hua & Wen (2004) show that, University of California Berkeley employees are more 
likely to  try and regularly use  a dynamic ridesharing service  than UC graduate students, or 
commuters  to  downtown  Berkeley.  Martin  &  Shaheen  (2011)  offered    perspective  on 
how public  transit and  non-motorized  modes may  change with car  sharing.  Liu,  Wu  &  Li 
(2018)  focused on a pervasive trend among Millennial consumers: the experience of benign 

Literature Review 
15 
 
envy toward others’ positive travel experience sharing on social networking sites. Lind et al. 
(2015) suggested that, the value-belief-norm  theory is  successful in  explaining travel mode 
choice in a Norwegian urban public when controlling for situational factors. Klöckner, Nayum  
& Mehmetoglu  (2013) analyzed how ownership of an electric car potentially impacts car use 
patterns. 
The expectancy theory focuses on  performance and effort, “right actions lead to the  desired 
outcomes” and  “the more  effort, the  higher  likelihood of  achieving the  desired outcomes.” 
Results of this study support the merger of the two theories (MacCallum, 1999). It may be 
necessary to study a wide range of behaviors which cannot all be observed or the behavior of 
interest has already occurred, or it may be unaffordable to observe the actual behaviour of large 
number of tourists (Juvan & Dolnicar 2016). Heo & Muralidharan (2017)  were not found  the 
moderating role  of  perceived  consumer  effectiveness    but it  did not   show  that consumer 
innovativeness amplifies the positive effect of hedonic value of collaborative consumption on 
attitude. Stach (2011) Examined the young consumer’s consumption and attitude to sustainable 
consumption. 
 
Despite the limited generalizability of the sample, Heo & Muralidharan (2017) suggested that, 
young  Millennials,  as  the  most  environmentally  educated  cohort,  are  more  likely  to  be 
influenced  by  environmental  knowledge  when  purchasing  green  products.  Steiger  (1990) 
seemed  to be a discrepancy between factors that affect attitudes and behavioral intentions: 
Perceived  sustainability  is  an  important  factor  in  the  formation  of positive  attitudes 
towards collaborative  consumption,  but  economic  benefits  are  a  stronger  motivator  for 
intentions to participate in CC. Charles & Kline (2006); Godelnik (2017) founded that, 50% 
of millennials agree that the sharing economy improves the American economy as a whole and 

Literature Review

explored the engagement of millennial students with the sharing economy via a project called

Buy Nothing New, Share Everything Month. Tanaka (1987); Chan & Shaheen (2012)

categorized North American ridesharing into five key phases: World War II car-sharing clubs;

major responses to 1970s energy crises; early organized ridesharing schemes; reliable

ridesharing systems; and technology-enabled ride matching. The confirmatory factor

analysis showed that the Geotraveler Tendency Scale provides a valid and reliable

measurement tool to determine if travelers to an area align with ecotourism’s definition (Boley,

Nickerson & Bosak 2010). Bentler & Chou (1987); Yin et al. (2018) investigated the motives

for participation in situated ridesharing and includes economic benefits, time

benefits, transportation.

2.4 Previous Study on SEM

A full structural equation model is composed of three set of equations (or three sub models):

(1) a measurement model for the endogenous (dependent) variables (2) a measurement model

for exogenous (independent) variables and (3) a structural model. However, a full SEM is

rarely applied in practice. An SEM measurement model is used to specify a set of latent

(unobserved) variables as linear functions of other observed endogenous or exogenous

variables. In a full SEM, structural model is used to capture the causal influences among the

latent exogenous and latent endogenous variables. If no measurement model is used, structural

model capture directly the causal influences of the observed exogenous variables on the

observed endogenous variables and the causal influences among observed endogenous

variables. SEM, that have measurement model only for observed endogenous variables,

structural model involves latent endogenous variables rather than observed endogenous

variables. Similarly, for SEM with measurement model only for observed exogenous variables,

Literature Review

structural model involves latent exogenous variables rather than observed exogenous variables.

An important step before model estimation is to ensure that each components of the model is

identified. Structural equation model is basically a set of simultaneous linear equations. To

obtain correct parameter estimates, the set of equations must be identified regardless of the

sample size. Model identification problem can be resolved by imposing some constraint on

model parameters. This restriction can be imposed by fixing some parameters value to a pre-

defined value or fixing some error terms to zero. If the reliability of on the measurement of a

observed variable is known, error term for that variable can be defined as (1- reliability) times

variance of the variable.

Methodology

CHAPTER THREE

METHODOLOGY

3.1 Introduction

In this chapter overall methodology is focused on SA of ride sharing service doing study of

ride sharing attitude and perceived risk using Structural Equation Modeling. First section

describes the brief steps of work. Subsequent section describes the specification of the SEM

with the hypothesis testing of the models.

3.2 Steps of Work

Questionnaire was set according to research objectives. Questionnaire was designed in the

google form for easily accessible for the user’s. Both personal info. and research related info.

was asked to the respondents. All the responses were combined in an excel sheet. Responses

data were then sorted 1 to 5 rating scale to make understand the analysis tool. At the same time

when the data were being collected, the method for hypothesis is being selected. Then the tools

(Amos 26) for hypothesis testing was selected. Data consistency and suitability for factor

analysis was determined. At the final stage several models were tested to justified the SA by

trial and error. Considering the model fit whether the relations are accepted or not is also

justified. And finally the best model is selected for SA justification. The overall flow diagram

is given in the Fig. 3.1.

Methodology

Fig. 3.1: Flow diagram of research work

3.3 Study Methodology

A three step Methodology is adopted for this research work. The first step aims at selection of

SA variables based on research objectives. The SA variables included in the survey with some

basic parameters.

Second steps give the data collection and data sorting for different data testing and also for

hypothesis testing.

Third step gives the structural equation models to utilize this study. Collected data is filtered

for anomalies and a series of models are developed to understand thoroughly the relationships

between overall SA of Ride Sharing service of different independent and dependent variables.

For each empirical model, the process of model development follows the approach of trial and

Methodology

error in terms of accommodating various exogenous, endogenous and latent variables as well

as overall goodness of fit values of the models.

3.3.1 Selection of SA variables

The models require input variables to be provided into the system which are the attributes or

features of SA affecting passenger’s satisfaction. The selection of concise sets of attributes is

a challenging task. Many researchers have used large number of attributes to model a specific

problem but that creates the problem of inputting too many variables into the system. Another

challenge is to identify and combine both commuter satisfaction and transit performance

measures. The use of a generic list of attributes for determining SA in any field of service but

the idea did not gain much appreciation from fellow researchers. Because many are in

agreement that various situation calls for separate analysis of each problem in hand and

attributes selected accordingly. The Transportation Research Board, developed different transit

service aspects for service quality measure, summarized in different reports. In these reports

five categories of service acceptance measures are defined: availability in terms of passengers‟

ease of access and use of ride service, travel time, safety and security in terms of real and

perceived chances of being involved in an accident or being the victim of a crime while using

transit, and maintenance and construction. For each service acceptance aspect some examples

of objective measures are suggested.

So, several studies and manual developed by research suggest categories of variables which

constitute the standard criteria for measuring SA. Most of the published studies found are from

developed countries. These findings are likely to be different from the context of developing

countries like Bangladesh.

Lack of indigenous literature has led to our derivation of SA variable for road passenger vessel

in Bangladesh from literature research, various focused group discussion, extensive

Methodology

brainstorming and expert opinion of academicians, practitioners. Then using this preliminary

designed questionnaire was conducted to get the feedback of respondents and check the

soundness of the survey design. Considering passenger’s opinion, the questionnaire is modified

accordingly before actual data collection.

After detailed investigation, a set of 20 SA variables were selected to carry out this research.

Table 3.1 shows the selected SA variables for this research.

Table 3.1: List of service acceptance variables

Variable

Category

Variable name

Variable

Annotation

Path Co-efficient

P-value

Endogenous

observed

variables

Comfortability

0.31

Time

Affordability

0.45

Cost

Affordability

0.41

Familiarity with

application

0.23

Convenience

0.49

***

Availability

0.24

Driver’s

Attitude

0.54

***

Result and Discussion

Driver’s skill

0.46

Traffic

Congestion

0.52

***

Environmental

Impact

y10

0.48

***

Personal Info.

y11

0.71

***

Account info.

y12

0.75

***

Waiting charge

y13

0.42

Passenger’s

safety

y14

0.38

Women’s safety

y15

0.37

Accident

y16

0.10

Deception

y17

0.15

Conflict risk

y18

0.05

Permission for

Ride Sharing

Y19

0.95

***

Allowing

personal car for

Y20

0.12

User’s

Judgement

η1

Result and Discussion

Latent

Variables

Safety &

Security

η2

0.63

***

Note: *p<0.05; **p<0.01; ***p<0.001

Permission for RS(Y1) service influence Allowing personal car(Y2) for RS with path co-

efficient 0.19 and p-value less than 0.02. Among Permission someone for RS and Allowing

personal car for RS Permission someone for RS influence Service Acceptance dependant

variable more positive with co-efficient 0.95. That means, permission someone for RS has

more influence on SA than Allowing personal car with co-efficient 0.12.

5.4 Empirical Model Results

Structural Equation Modeling is used to analyse Service Acceptance of Ride Sharing service

in Bangladesh. The target of this analysis is to reveal parameters which represents the main

aspects of SA. A series of models are developed to thoroughly identify the relation between

independent variables, dependent variables & Latent variables. Initially a model is proposed

randomly and after that the model is re-examined several times to modify and to form a better

acceptable model. For this trial & error method is done.

The model reveals the relationship of variables with each-other considering different

parameters. Hooper et al. (2008) introduce a guideline for determining model fit indices.

Absolute fit indices determine how well a certain model fits the sample data. The value of CFI,

NFI, TLI, RMSEA, AIC and x2/df is given below table 5.6. According to Marsh et. Al. (2004)

CFI value closer to 1.0 is indicates a good fit. And RMSEA value less than 0.05 is considered

as very good fit (Steiger 1990). And the x2/df value below 3.00 is acceptable. And PNFI value

less than 0.500 is acceptable.

Result and Discussion

Table 5.7: Goodness of fit measures of models

Fit Indices

Value

Incremental Fit

CFI

0.869

NFI

0.841

TLI

0.811

PNFI

0.478

Absolute Fit Indices

RMSEA

0.063

X2/df

481.941

175

Result and Discussion

X2/df

2.75

Ride Sharing service not only impact the transport system of our country but also impact user’s

psychological condition. Sometimes users have to share his/her rides with someone who is

below/above than his/her status. At this situation user’s comfortability works a lot. From our

user’s response we have found the user’s comfort during sharing ride which is given below in

Fig. 5.3.

Fig. 5.3: Comfortability of user’s during sharing his/her rides

Time management is a concern issue for our country. Traffic jam killing our valuable time.

Passengers can’t reach to destination in due time. Another problem is that our bus has a

particular route they can’t divert to other route. But, ride sharing transports can choose any

route they want to. Time affordability of ride sharing service is given below in Fig. 5.4.

Result and Discussion

Fig. 5.4: Time affordability during peak hour

Ride sharing service main purpose is to travel at any place at low price. But the fare of public

transport is low than ride sharing service fare. How this slightly fare of ride sharing service is

affordable is given in Fig. 5.5.

Fig. 5.5: Cost affordability while sharing the rides with others than travelling alone

Result and Discussion

Application operations is the main concern of this ride sharing service. There are few ride

sharing applications. How people are familiar with these apps are given below in Fig. 5.6.

Fig. 5.6: Familiarity with ride sharing application

During peak hour there is always a vehicle scarcity. Because both office hour & school hours

are coinciding with each-other. Availability of ride sharing vehicles are shown in chart below

in Fig. 5.7.

Fig. 5.7: Availability of ride sharing vehicles during peak hour

Result and Discussion

The roads of Dhaka city and all other cities are very congested. Bus and other vehicles can’t

pass freely. In this situation drivers with no basic knowledge of driving drive bus at their will

which occur frequent accident. But Ride Sharing service vehicles are more likely to be personal

cars with skilled driver’s. Overall driver’s skills of driver are given below in Fig. 5.8.

Fig. 5.8: Driver’s skill both in free flow & congested condition

Traffic congestion of ride sharing services during peak period are given below in Fig. 5.9.

Fig. 5.9: Traffic congestion during peak hour

Result and Discussion

Most of the vehicles in our country use fuel which is very harmful for our environment. Ride

sharing service use Environmental friendly fuel in Fig. 5.10 which is very effective for

environment.

Fig. 5.10: Environmental impact due to use of fuel

In ride sharing service fare is paid by any method (cash, bKash, credit card etc.). By paying the

fare by any online payment method gives the account info. of users. How respondents support

this are given below in Fig. 5.11.

Fig. 5.11: Support “Ride Sharing” services as it takes credit card/bKash/Rocket account info.

Result and Discussion

Most of the ride sharing vehicles are owned by any person who use the vehicle for his/her

personal need. There are few owners who are not willing to allow their personal car for ride

sharing. Fig. 5.12 shows that very less owners are willing to allow their car for ride sharing.

Fig. 5.12: Allowing personal car for “Ride Sharing” service while it remains idle.

Safety of ride sharing service is given below in Fig. 5.13.

Fig. 5.13: Overall safety of “ride Sharing” service

Result and Discussion

Women are working parallel with men. They aren’t lagging behind any more. But working late

night and return safely at home has become a concern issue now a day. From Fig. 5.14 we can

say that, ride sharing service also provide safety for women travelling at night.

Fig. 5.14: Women safety during sharing her rides at night

Safety is a very concern thing. In public there are frequent accident of passengers and also the

vehicles with each-other. Fig. 5.15 shows that, ride sharing vehicles have less accident trend.

Fig. 5.15: Possibilities of accident while using “Ride Sharing” service

Result and Discussion

In public transport there are always a chance for the new or old passengers to be deceived by

the contractor due to fare rate. Contractor demand extra fair and sometimes this situation turns

into hazardous situation. In Ride Sharing service there is no possibilities to being deceived as

the fare system is done by mobile applications. Drivers can’t demand extra fair as the fair is

shown or displayed before starting the ride. In Ride Sharing service if any passengers get

deceived he/she can report on that. So, from Fig. 5.16 we can say that, there is less possibilities

to being deceived.

Fig. 5.16: Possibilities of being deceived due to fare payment.

Ride sharing main purpose is to share someone’s ride for reducing fare pressure by paying the

fare equally. Sometimes there are possibilities of conflict among the passengers. Sometimes,

passengers are unwilling to pay the exact fare, sometimes passengers feel that they have shared

the ride after a certain distance and according to that they should pay less. This kind of

mentalities cause conflict among the passengers. Conflict between the passengers and drivers

can also be occurred. Sometimes drivers don’t come to the exact pick-up point, passengers

have to walk certain distance which cause conflict between passengers and drivers. One the

Result and Discussion

other hand route changing drop-out at different point also cause conflict. Sometimes fare is

increased due to unwanted traffic jam which also cause conflict among the passengers and

drivers. Conflict of ride sharing service is given below in Fig. 5.17.

Fig. 5.17: Possibilities of conflict while paying the fare among the user’s.

5.5 Discussion

This paper verifies a structural model to identify the Ride Sharing SA considering passenger’s

attitude and perceived risk.KMO and Bartlett's test was done in order to validate the data

sufficiency for factor analysis purpose. The result of KMO and Bartlett’s shows the data

suitability for factor analysis. We have done both EFA and CFA which gives convergent

validity and divergent validity of sample data. A reliability test of CFA also done for the sample

data. Cronbach’s alpha test tell us that data is consistent for factor analysis.

The result of model shows the overall service acceptance of this Ride Sharing service with

CFI>0.80 and RMSEA<0.08. All the variables have positive influence on SA of Ride Sharing

service. Personal info. has negative influence with women’s safety. From our perception we

Result and Discussion

assumed the information RS service is taking may have safety concern of women travelling

specially at night. From our co-efficient value our perception proved as wrong. Info. provided

by RS service has inverse influence on women’s safety. User’s Judgement has positive

influence on permission someone for Ride Sharing. If someone’s satisfaction level is fulfilled,

he/she will give permission someone for sharing his/her ride. Permission someone for RS has

positive influence on SA of RS service.

The experience of passengers in these ride sharing services is instrumental in determining

whether they continue to use these services and how frequently. And for this Comfortability

during sharing ride, Time Affordability, Cost Affordability, Familiarity with Ride Sharing

applications, Availability during peak hour, Drivers skill, Traffic Congestion, Environmental

Impact, Safety for all the passengers, Women safety specially during night travelling,

Deception and conflict among the passengers & with the drivers play a major role. Analysing

our respondents both who have used or haven’t used ride sharing service we found that, ride

sharing attitude are significantly associated with those parameters. From that analysis we also

found that, passengers will feel comfort to share his/her ride as ride sharing as this service

appear to them as a Time Affordable & Cost Affordable service. Due to lack of basic

knowledge of mobile operation ride sharing application seems un-familiar to them. Our result

also indicates that, there is lack of ride sharing vehicles during peak hour but still passengers

prefer this service as faster movement with skilled drivers.

Transport has great impact on environment. Using of un-environmental friendly fuel cause

great damage to environment. Our Ride Sharing service transports use environmental friendly

fuel which is preferable by all. As this service based on both manual and mobile banking

payment system so passengers sometimes doesn’t support this system.

Result and Discussion

Safety is a great concern for passengers in our country. Our public transport has overtaking

tendency to get more passengers than others which cause sometimes major fatalities to

passengers. Specially, women travelling public transport at night is a great concern. Several

unusual occurrence has been occurred in past days. According to our respondents Ride Sharing

service seems more secure transport system than public transport. They also think this service

even safer for women at night.

These result shows that, there are still some factor in which passengers can’t bring full trust on

it. But overall considering this service with public transport system both users and non-users

prefer this service.

More heterogeneity of this study can be done by analysing the model by the variation of

Gender, Age and Monthly Income.

Conclusions

CHAPTER SIX

CONCLUSIONS AND RECOMENDATIONS

6.1 Introduction

This study is an attempt to model the causal relationship between overall SA of the sharing

passenger vessel operating in different routes of Bangladesh and SA variables describing the

attitude and perceived risk of ride sharing service. The service users stated preferences are used

to find out the significant variables those affect the SA most. For this purpose, SEM is used.

SEM is a multivariate analysis technique which can expose the inherent structure within a set

of data and permits to introduce latent constructs.

6.2 Conclusions

The aim of this research was to justify the user’s attitude to share their rides with each other

travelling at the same destination considering perceived risk and others attributes. Our study

reveals that user’s have high tendency to share their rides with each other. Best structure for

understanding Service acceptance of ride sharing service is provided in this research using

SEM. It reflects passenger demand on overall Ride sharing service through their perception

about sharing attitude and perceived risk variables. Individual passenger specific observations

are used for modeling which reflect their needs and expectations. To identify the structure that

suits Ride Sharing service acceptance data, different SE models are developed and one model

is selected by trial and error. Models goodness of fit is justified by different parameters(CFI>

0.80 and RMSEA< 0.08) and consistency with real life expected scenario.

Conclusions

Following conclusions are obtained from the best model:

KMO and Bartlett's test result is greater than 0.5 which means the suitability of data for factor

analysis. From cronbach’s alpha test data is suitable for factor analysis. For Confirmation

Factor Analysis, CFI= 0.833 and RMSEA=0.062 which denotes the goodness fit of model. RS

service provide enough safety on personal information so, there need not to be worried about

the passenger’s safety specially women’s safety during night travel. To user’s ride sharing

service is more comfortable than any other public transport service. Despite of less availability

users prefer this service as Time affordable service and cost affordable service than other

transport like CNG and rickshaw. There is less possibilities of accident and it is safer for

women than public transport. And there are no chances of being deceived by drivers and

passengers due to fare.

Considering both sharing attitude and perceived risk ride sharing service is an emerging service

in our country and it also satisfies all the demands of user’s. Proper management can lead our

transport system to a new dimension.

6.3 Recommendations for Future Research

The heterogeneity among users might affect ride sharing SA differently. SA variables are not

equally judged by the users; meaning that an improvement made to any of these variables

would not have the same acceptance level from the individual users. This effect can be

examined by revaluating the model, by dividing the entire sample based on gender, age,

monthly income, route etc. The author expects to develop further refined models for Ride

sharing SA, that would be a far of this debate. After that, driverless vehicles controlled centrally

should be implemented for better experience.

Conclusions

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Examining the Antecedents of Using Ride-Hailing Services: A Study in Dhaka City of Bangladesh

Article

Full-text available

Jul 2020

The trend of using apps based ride-hailing service has continuing to rise in the last few years. Ride-hailing services are becoming increasingly common in Dhaka, the capital of Bangladesh. The advent of this technology not only provides relief to people used to spending hours in congested traffic, but it also creates opportunities for thousands of unemployed youth. The aim of this study is to examine the behavioral intention of using ride-hailing apps services among commuters in Dhaka city. Technology acceptance model (TAM) is employed. A total of 250 data were received from the respondents living in the Dhaka city who have been using this apps service. The data were analyzed by using SPSS and AMOS version 21.0. The result indicates that satisfaction has a significant influence on behavioral intention to use ride-hailing apps. The findings further reveal that perceived usefulness have a significant impact on both satisfaction and behavioral intention. On the other hand, perceived usability found to be insignificant in determining the relationship with satisfaction and behavioral intention. Additionally, perceived trust is positively associated with satisfaction but negatively with behavioral intention. The findings from this study will enhance service providers involved in this operation to understand the best policy which should be taken in order to serve commuters better.

Bus Service for 'Women Only' in Dhaka City: An Investigation

Article

Full-text available

Dec 2010

M. Shafiq-Ur Rahman

Public buses in Dhaka City are inadequate in numbers and mostly remain overcrowded which is not accessible for many people, particularly the elderly or disabled and the women. Considering the travel problems of women, in the early 1980s Bangladesh Road Transport Corporation (BRTC) had provided services of 'women only' bus (called 'women-bus'). However, the operation was stopped immediately after some days of its inauguration. Later on, in several times, BRTC initiated similar project but could not survive for various reasons. Lastly, again in July 2008, only 5 buses have been launched in one route for 'women-only' bus service. This paper explores the existing route, frequency, and service quality of the 'women-only' bus and investigates why this service could not survive in the past or lessons learnt from the previous failures. The 'women-only' bus service was observed and interviews of the passengers have been done for exploring the existing situation of the service whilst a Focus Group Discussion (GFD) was done for investigating transportation problems of women, their perception about 'women-only' bus service, and expectations about the service. The success of 'women-only' bus service may provide insights for expansion or improvement of the service, which in turn could help solving the transportation problems of women.

Modeling Americans’ autonomous vehicle preferences: A focus on dynamic ride-sharing, privacy & long-distance mode choices

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Jan 2020
TECHNOL FORECAST SOC

Rapid advances in technologies have accelerated the timeline for public use of fully-automated and communications-connected vehicles. Public opinion on self-driving vehicles or AVs is evolving rapidly, and many behavioral questions have not yet been addressed. This study emphasizes AV mode choices, including Americans’ willingness to pay (WTP) to ride with a stranger in a shared AV fleet vehicle on various trip types and the long-distance travel impacts of AVs. Exactly 2,588 complete responses to a stated-preference survey with 70 questions provide valuable insights on privacy concerns, safety and dynamic ride-sharing with strangers, long-distance travel and preferences for smarter vehicles and transport systems. Two hurdle models (which allow for a high share of zero-value responses) were estimated: one to predict WTP to share a ride and another to determine WTP to anonymize location while using AVs, and a multinomial logit was developed to estimate long-distance mode choices with AVs and SAVs available. Results suggest that WTP to share rides will rise over time, for a variety of reasons, and SAV use will be particularly popular for long-distance business travel. Elasticity estimates suggest that privacy may not be an important concern for AV-based travel.

Discriminatory Attitudes Between Ridesharing Passengers

Article

Full-text available

Oct 2020
TRANSPORTATION

Prior studies have provided evidence of discrimination between drivers and passengers in the context of ridehailing. This paper extends prior research by investigating passenger-to-passenger discriminatory attitudes in the context of ridesharing. We conducted a survey of 1,110 Uber and Lyft users in the US using Mechanical Turk, 76.5% of whom have used uberPOOL or Lyft Shared rides, and estimated two structural equation models. The first model examines the influence of one's demographic, social and economic characteristics on discriminatory attitudes toward fellow passengers in ridesharing, and how such influence varies by the targets of discrimination (i.e., race and class). The second model examines the influence of one's generic social dominance orientation on discriminatory attitudes in the ridesharing context. We find that discriminatory attitudes toward fellow passengers of differing class and race in the shared ride are positively correlated with respondents that are male or are women with children. A respondent's race does not have a significant effect on discriminatory attitudes, but white respondents that live in majority white counties are more likely to hold discriminatory attitudes with regard to race (no effect is observed regarding class preferences). The same is true of respondents that live in counties in which a larger share of the electorate voted for the Republican candidate in the 2016 presidential election. Conversely, higher-income respondents appear more likely to hold discriminatory attitudes regarding class, but no effect is observed regarding racial preferences. We also find that one's generic social dominance orientation strongly influences his/her discriminatory attitudes in ridesharing, supporting the claim that behavior in shared mobility platforms reflects long-standing social dominance attitudes. Further research is required to identify policy interventions that mitigate such attitudes in the context of ridesharing.

Rider-to-rider discriminatory attitudes and ridesharing behavior

Article

Full-text available

Apr 2019
TRANSPORT RES F-TRAF

Using online survey data from N = 2041 Uber and Lyft users in the United States collected in 2016 and 2018, this paper establishes the validity, reliability, and invariance of a measure of rider-to-rider race and social class discrimination. This measure is then incorporated into three structural models that investigate associations between rider-to-rider discriminatory attitudes and four aspects of ridesharing behavior. We find no significant relationship between rider-to-rider discriminatory attitudes and whether a TNC user has ever used a ridesharing service (such as uberPOOL or Lyft Line). However, among those who have used ridesharing services before, rider-to-rider discriminatory attitudes are strongly negatively predictive of an individual's level of satisfaction with the sharing option, and marginally negatively predictive of an individual's percentage of shared TNC trips. Furthermore, among those who have not yet used ridesharing services, rider-to-rider discriminatory attitudes are strongly negatively predictive of willingness to consider using uberPOOL or Lyft Line in the future. Together, these findings suggest that rider-to-rider discriminatory attitudes may discourage sustained and frequent use of ridesharing services among TNC users. Further research is required to identify strategies for addressing discriminatory attitudes in the ridesharing context and overcoming reluctance to sharing.

Bus Services in Dhaka City - Users’ Experiences and Opinions

Article

Dec 2012

Buses are the only available organized mass public transport system in Dhaka. However, the city is planning to have bus rapid transit (BRT) systems and metro systems to cater the increasing demand for public transport. The buses in Dhaka mostly remain over-crowded, which is often not accessible for the elderly or disabled people as well as for the women. Moreover, the frequency of bus service (headway) is not good. The paper reports the existing service and the users’ opinion about the service level of public bus operating within the city. For this purpose, 5 different bus routes had been chosen and a total of 175 passengers of bus (30 from each route) had interviewed with a pre determined structured questionnaire to know their experience/satisfaction and opinion about the existing service as well as their expectations. Surprisingly, it was found that most of the respondents are satisfied with the cost of ticket but very unsatisfied with the waiting time as they have to wait for the bus sometimes about an hour. Journal of Bangladesh Institute of Planners, Vol. 5, Dec 2012, pp. 93-105

The Gender Earnings Gap in the Gig Economy: Evidence from over a Million Rideshare Drivers

Article

Nov 2020

The growth of the “gig” economy generates worker flexibility that, some have speculated, will favor women. We explore this by examining labor supply choices and earnings among more than a million rideshare drivers on Uber in the United States. We document a roughly 7% gender earnings gap amongst drivers. We show that this gap can be entirely attributed to three factors: experience on the platform (learning-by-doing), preferences and constraints over where to work (driven largely by where drivers live and, to a lesser extent, safety), and preferences for driving speed. We do not find that men and women are differentially affected by a taste for specific hours, a return to within-week work intensity, or customer discrimination. Our results suggest that, in a “gig” economy setting with no gender discrimination and highly flexible labor markets, women’s relatively high opportunity cost of non-paid-work time and gender-based differences in preferences and constraints can sustain a gender pay gap.

Road network structure and ride-sharing accessibility: A network science perspective

Article

Mar 2020
COMPUT ENVIRON URBAN

The prosperity of ride-sharing services has rippled in the communities of GIScience, transportation, and urban planning. Meanwhile, road network structure has been analyzed from a network science perspective that focuses on nodes and relational links and aims to predictive models. However, limited empirical studies have explored the relationship between road network structure and ride-sharing accessibility through such perspective. This paper utilizes the spatial Durbin model to understand the relationship between road network structure and ride-sharing accessibility, proxied by Uber accessibility, through classical network measures of degree, closeness, and betweenness centrality. Taking the city of Atlanta as a case study, we have found in addition to population density and road network density, larger values of degree centrality and smaller values of closeness centrality of the road network are associated with better accessibility of Uber services. However, the effects of betweenness centrality are not significant. Furthermore, we have revealed heterogeneous effects of degree centrality and closeness centrality on the accessibility of Uber services, as the magnitudes of their effects vary by different time windows (i.e., weekday vs. weekend, rush hour in the morning vs. evening). Network science provides us both conceptual and methodological measures to understand the association between road network structure and ride-sharing accessibility. In this study, we constructed road network structure measures with OpenStreetMap, which is reproducible, replicable, and scalable because of its global coverage and public availability. The study resonates with the notion of cities as the set of interactions across networks, as we have observed time-sensitive heterogeneous effects of road network structure on ride-sharing accessibility.

The satisfaction of tourists using bicycle sharing: a structural equation model - the case of Hangzhou, China

Article

Feb 2020

This study explores the impacts of bicycle sharing and the satisfaction of tourists using such services. Using Hangzhou as a case study and data derived from 552 tourist surveys, a structural equation model of the satisfaction of tourists using bicycle sharing is constructed. Six perceptual factors were identified as sources of tourist satisfaction arising from the use of a cycle sharing scheme, namely: cycle accessibility, perceived risk, environmental awareness, psychological benefit, managerial action, and perceived rule adherence. Of these, tourists’ psychological benefits accounted for the highest proportion of tourists’ satisfaction, followed by easy access to cycles, environmental awareness, and management effectiveness. Rule adherence and risk perception exerted relatively less influence. A significant positive correlation was noted between usage satisfaction and environmental awareness, perceived rule adherence, ease of access to cycles, psychological benefit, and managerial action. However, the research hypothesis that perceived risk affects tourist satisfaction was not supported by the study findings. Finally, this study suggests some bicycle sharing management strategies and recommendations to enhance tourists’ usage satisfaction.

Understanding consumers’ willingness to use ride-sharing services: The roles of perceived value and perceived risk

Article

Aug 2019
TRANSPORT RES C-EMER

In order to popularise the sustainable transport innovation of ride-sharing, it is critical for service providers and policymakers to understand the factors affecting ride-sharing willingness of potential users. This research explores the drivers of non-users’ willingness to use ride-sharing services from the perspectives of perceived value and perceived risk, where perceived value and perceived risk are both conceptualised as formative second-order constructs constituted by their first-order value components and risk components. The data was collected in China through an online questionnaire from 378 respondents who had never used a ride-sharing platform. Partial least squares structural equation modelling (PLS-SEM) is used to verify the research model and hypotheses. The empirical results reveal that perceived value is positively associated with consumer willingness to participate in ride-sharing, but perceived risk is negatively related to consumers’ ride-sharing intention. Contrary to expectations, perceived risk positively moderates the effect of perceived value on consumers’ ride-sharing intention. This study contributes to a deeper understanding of the effects of consumers’ value perception and risk perception on their acceptance of internet-based ride-sharing services. Measures to promote ride-sharing include maximising consumers’ value of ride-sharing and their perception of value as well as reducing potential risks in ride-sharing process.

ACCEPTANCE OF RIDE SHARING SERVICE BY STRUCTURAL EQUATION MODELING

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